The present invention relates to handwriting capture devices, and more specifically to a method for verifying a handwritten signature entered into a digitizer.
The method of the present invention has particular application in conjunction with the method disclosed in the co-pending application by Crooks et al., in which a handwritten signature is captured at a point of sale, compressed, and stored for later use to authenticate the transaction. Strokewise data compression is accomplished by examining the coordinate data on a sequential basis in accordance with the ordered storage arrangement thereof. A digital computing device progressively selects start points and stop points and examines the coordinates of all midpoints situated therebetween, where midpoints are defined as points located in time between the start and stop points. The computing device establishes guidelines between the start points and their associated stop points and selectively saves the coordinate data only for those midpoints which are not situated at predetermined locations relative to their associated guidelines. Midpoints which are situated at predetermined locations are considered to be redundant and are discarded.
The preferred method disclosed by Crooks et al. for saving and discarding data is a linear fit criterion. A straight line is established between each start point and the successively established stop points. The equation of the straight line between the start point and the stop point is calculated in terms of a slope and a Y-intercept. For each examined midpoint, the X coordinate thereof is substituted into the equation for the line, and the line equation is solved to determine a Y value. The calculation is performed using floating point arithmetic, and the result is converted to an integer. If the resulting integer value of Y is within a predetermined limit of the Y coordinate of the point being examined, based upon the amount of scaling provided, then the rejection criterion is satisfied. The scaling factor represents a desired reduction in resolution for the resulting data and provides an inherent threshold for accepting or rejecting midpoints.
Crooks et al. disclose an alternative embodiment which utilizes a rejection criterion which is based upon a calculated perpendicular distance between a midpoint under examination and a straight line between the start point and the stop point. The calculated distance is compared with a predetermined threshold distance to either accept or reject the midpoint.
The method of the present invention also builds upon the method for recording compressed data disclosed by Wagner et al. The method includes a perpendicular test as well as a parallel test for discarding handwritten data points relative to a series of guide lines. The parallel test determines whether a data point lies at a true distance within a predetermined threshold distance either side of the guide line. The perpendicular test determines whether the data point lies between two perpendicular lines through the end points of the guideline. Both tests must be satisfied before a data point is discarded. Floating point arithmetic, with its inherent inaccuracy and its associated excessive processor cycles, is avoided by using integer scaling and a predetermined parallel threshold value. To further reduce the compressed signature size, the x and y delta values, which are used to denote points within a stroke, are shortened. Error is maintained at a predetermined limit by adjusting the delta values prior to storage.
Merchandising systems used in conjunction with the method described in the above-mentioned patent applications may be equipped with a transparent glass screen having a resistive coating fused to its surface. A linearized voltage field is established on the surface of the screen. A human signature is captured by providing a hand-held stylus which is moved across the surface of the screen during writing of the signature. A digitizer senses the position of the stylus during writing of the signature and generates digital signals representing the X-Y coordinates of the stylus. The digitized coordinates are stored in a memory and are also used to drive a liquid crystal display positioned below the glass screen. This produces a visual display of the signature, as the handwriting progresses. Means are provided for maintaining the signature in registration with the movement of the stylus. An example of such a device is disclosed by Allgeier et al.
Signature capture methods are typically intended to minimize credit card fraud, which is a serious problem for merchants. Credit cards and credit card numbers are easily obtained and exploited to the loss of credit card companies. With the advent of handwriting capture devices, the signature of a credit card user may be captured and verified while a credit transaction is taking place. A reference signature may be obtained from a SMART card through a PIN number or a database through either the SMART card PIN number or credit card account number assigned to the user.
Previous signature verification methods require that all of the digitized signature points and their corresponding timing data be input into the verification system. These methods require expensive digitizers, robust and expensive processors, and large amounts of memory, and they employ slow and complicated algorithms which implement functions requiring many floating point arithmetic operations.
Therefore, it would be desirable to provide a method for processing a handwritten signature which is less expensive to implement than previous methods, employs simpler algorithms than previous methods, and which requires fewer points than previous methods, but which yields a high degree of accuracy.